def tuneParamenters():
numberOfPoints = 5
numberOfRounds = 1
branchDepth,bridgingDepth, msaWidth = 1 , 10 , 10
headerName = "synthetic_reads\\"
listOfNLKDataPts = logging.loadingLNKFile(headerName)
resultList = []
for index in range(numberOfPoints):
N, L = listOfNLKDataPts[index][1], listOfNLKDataPts[index][2]
print N, L
for roundNum in range(numberOfRounds):
folderName = headerName + "sample_point_"+ str(index) +"\\round_"+str(roundNum) +"\\"
branchClearingUnitTest(folderName, branchDepth)
numMistakes, success = ECUnitTest(N, L, folderName,bridgingDepth, msaWidth )
resultList.append([N, L, roundNum , numMistakes, success])
print "resultList", resultList
logging.logBatch(resultList)
def batchProcessingLNKTest():
print "Batch Processing LNK Test"
headerName = "synthetic_reads/"
os.system("mkdir " + headerName)
logging.savingLNKFile(headerName)
listOfNLKDataPts = logging.loadingLNKFile(headerName)
numberOfRounds = 1
listOfNLKDataPts = [listOfNLKDataPts[0]]
for testPoint, roundNum in zip(listOfNLKDataPts,
range(len(listOfNLKDataPts))):
folderName = headerName + "sample_point_" + str(roundNum)
os.system("mkdir " + folderName)
snpRate, typeOfGen, detail = 0.001, 'm', "500-200-50"
[
G, N, L, p, epsilon, K, liid, threshold, NKcov, Nbridge, Ncov,
ratio, numberOfClusterRounds, brachingDepth, bridgingDepth,
msaWidth, clusterRounds, fingerPrint, clusterRatio
] = testPoint
parameterRobot = logging.parameterObj(
G, N, L, p, epsilon, K, liid, threshold, NKcov, Nbridge, Ncov,
ratio, numberOfClusterRounds, brachingDepth, bridgingDepth,
msaWidth, folderName, clusterRounds, fingerPrint, clusterRatio)
parameterRobot.indel = True
batchProcessingUnitTest(numberOfRounds, parameterRobot, snpRate,
typeOfGen, detail)
def tuneParamenters():
numberOfPoints = 5
numberOfRounds = 1
branchDepth, bridgingDepth, msaWidth = 1, 10, 10
headerName = "synthetic_reads\\"
listOfNLKDataPts = logging.loadingLNKFile(headerName)
resultList = []
for index in range(numberOfPoints):
N, L = listOfNLKDataPts[index][1], listOfNLKDataPts[index][2]
print N, L
for roundNum in range(numberOfRounds):
folderName = headerName + "sample_point_" + str(
index) + "\\round_" + str(roundNum) + "\\"
branchClearingUnitTest(folderName, branchDepth)
numMistakes, success = ECUnitTest(N, L, folderName, bridgingDepth,
msaWidth)
resultList.append([N, L, roundNum, numMistakes, success])
print "resultList", resultList
logging.logBatch(resultList)
def batchProcessingLNKTest():
print "Batch Processing LNK Test"
headerName = "synthetic_reads/"
os.system("mkdir "+headerName)
logging.savingLNKFile(headerName)
listOfNLKDataPts = logging.loadingLNKFile(headerName)
numberOfRounds = 1
listOfNLKDataPts = [listOfNLKDataPts[0]]
for testPoint,roundNum in zip(listOfNLKDataPts, range(len(listOfNLKDataPts))):
folderName = headerName+"sample_point_" + str(roundNum)
os.system("mkdir " + folderName )
snpRate, typeOfGen , detail = 0.001,'m', "500-200-50"
[G, N, L, p, epsilon, K, liid, threshold,NKcov, Nbridge, Ncov, ratio, numberOfClusterRounds,brachingDepth,bridgingDepth,msaWidth,clusterRounds, fingerPrint, clusterRatio ] = testPoint
parameterRobot = logging.parameterObj(G, N, L, p, epsilon, K, liid, threshold,NKcov, Nbridge, Ncov, ratio, numberOfClusterRounds,brachingDepth,bridgingDepth,msaWidth,folderName,clusterRounds, fingerPrint, clusterRatio )
parameterRobot.indel = True
batchProcessingUnitTest(numberOfRounds,parameterRobot,snpRate, typeOfGen , detail)
